Outsourced R&D and GDP Growth Anne Marie Knott

Transcript:Outsourced R&D and GDP Growth Anne Marie Knott:
Outsourced R&D and GDP Growth Anne Marie Knott Olin Business School Washington University XXII Organization Science Winter Conference February 6, 2016 I gratefully acknowledge support under NSF Award 1246893: The Impact of R&D Practices on R&D Effectiveness, and NSF Award 0965147: Firm IQ: A Universal, Uniform and Reliable Measure of R&D Effectiveness DISCLAIMERS: Any opinions and conclusions expressed herein are those of the author(s) and do not necessarily represent the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. I have a financial interest in amkANALYTICS, a subscription database of firm RQs. Romer (1990) provides first formal theory linking R&D to growth Finished goods production function: Y=Ka(ALY)1-a Imbedded in that is the knowledge production function: A’=dALA Where: A = knowledge/technology d = research productivity LA= research labor Combining: Y=Ka((A+dALA)*LY)1-a Most important conclusions: Growth in steady state: gA=gY=A’/A=(dALA)/A=dLA Testable proposition: doubling LA doubles g (Scale effects) The puzzle Scientific labor (LA) has increased 2.5x GDP growth declining 0.03% per year Two explanations for the disconnect* Jones (1995) explanation R&D has gotten harder Eliminates scale effects prediction, by adding Fishing out effect, q, - probability of finding new idea is declining in the stock of ideas Diminishing returns to scientific labor, l, -due to higher likelihood of duplicate efforts Revision: Implication: growth converges to 0 Alternative explanation Firms have become worse at R&D Scientific labor productivity, d, has declined Leave Romer intact Implication: Steady state growth Scale effects Third explanation is extension of first Paper tests the two explanations Characterize firms’ R&D productivity (RQ) Conduct semi-critical test of two explanations Identify source of declining RQ Demonstrate sufficient to account for decline Rule out alternative explanations linking source to declining RQ Speculate why it causes decline in RQ Speculate why firms persist with it RQ is most intuitive measure you could construct for R&D productivity Derived from production function: Y = Ka Lb Expand it to include intangibles: Outputit = Capitalita *Laboritb * R&Dit-1g * Spilloversit-1d* Advertisingite Matches most common approach to measuring R&D productivity (Hall, Mairesse, Mohnen 2010) Make all exponents firm-specific: Outputit = Capitalitai *Laboritbi * R&Dit-1gi * Spilloversit-1di* Advertisingitei RQ is the exponent, gi, on R&D Exact definition: “firm-specific output elasticity of R&D” % output increase from 1% R&D increase Important properties of RQ Universal: Can estimate for all firms doing R&D (only 50% of R&D firms patent) Uniform: It’s